Analysis of Trends in Liberal Arts Music Research at Korean Universities Using Text Mining

Objectives The purpose of this study is to analyze the academic papers related to liberal arts music education in Korean universities published to date through text mining techniques to examine the trends of the research and to suggest expansive discussions and directions for the field. Methods This study extracted a total of 1650 identity keywords based on the abstracts of published/candidate articles from 2007, the year of initial publication (Searched on RISS), to May 2024, and conducted text mining analyses such as frequency analysis, network centrality analysis, and LDA topic modeling. Results The results of the study are as follows: First, in the keyword frequency analysis using TF, TF-IDF, and N-gram, influential keywords included ‘music,’ ‘education,’ ‘class,’ ‘teaching-learning,’ ‘activity,’ ‘personality,’ ‘appreciation,’ and ‘convergence.’ Second, in the centrality analysis, ‘music,’ ‘education,’ ‘teaching-learning,’ ‘activity,’ ‘class,’ and ‘college students’ appeared as top keywords with similar levels of centrality. Third, based on the three topics extracted through LDA topic modeling analysis, the themes and topic names were set as follows: The design of classes and teaching-learning related to liberal arts music education, the direction of education, and the impact and empirical evidence of education. Conclusions Efforts are needed to enhance the future-oriented value and utility of university liberal arts music education by expanding the category and area of research through continuous studies, which are essential to respond to the social and educational changes in the Era of the Fourth Industrial Revolution and the Digital Age.